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IEEE International Conference on robotics and Automation (ICRA)

作者： Caiyue Xu Changming Zhang Yanmin Zhou Zhipeng Wang Ping Lu Bin He Department of Control Science and Engineering College of Electronics and Information Engineering Tongji University Shanghai China National Key Laboratory of Autonomous Intelligent Unmanned Systems Shanghai China Frontiers Science Center for Intelligent Autonomous Systems Shanghai China

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Collaboration between humans and robots is becoming increasingly crucial in our daily life. In order to accomplish efficient cooperation, trust recognition is vital, empowering robots to predict human behaviors and make trust-aware decisions. Consequently, there is an urgent need for a generalized approach to recognize human-robot trust. This study addresses this need by introducing an EEG-based method for trust recognition during human-robot cooperation. A human-robot cooperation game scenario is used to stimulate various human trust levels when working with robots. To enhance recognition performance, the study proposes an EEG Vision Transformer model coupled with a 3-D spatial representation to capture the spatial information of EEG, taking into account the topological relationship among electrodes. To validate this approach, a public EEG-based human trust dataset called EEGTrust is constructed. Experimental results indicate the effectiveness of the proposed approach, achieving an accuracy of 74.99% in slice-wise cross-validation and 62.00% in trial-wise cross-validation. This outperforms baseline models in both recognition accuracy and generalization. Furthermore, an ablation study demonstrates a significant improvement in trust recognition performance of the spatial representation. The source code and EEGTrust dataset are available at https://***/CaiyueXu/EEGTrust.

关键词： Adaptation models Computer vision Solid modeling Accuracy Source coding Brain modeling Transformers

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Enhancing the performance of CaTiO3-GDC heterostructure electrolytes in LT-CFCs

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Ceramics International 2025年第15期51卷 20131-20142页

作者： Li, Dongchen Cui, Yingying Hong, Xiaofang Shah, M.A.K. Yousaf Mushtaq, Naveed Rauf, Sajid Arshad, Naila Irshad, Sultan Alodhayb, Abdullah N. Yousaf, Muhammad Lu, Yuzheng Department of Electrical and Automation Shandong Labor Vocational and Technical College Jinan250300 China Jiangsu Provincial Key Laboratory of Solar Energy Science and Technology/Energy Storage Joint Research Center School of Energy and Environment Southeast University No.2 Si Pai Lou Nanjing210096 China College of Mechatronics and Control Engineering Shenzhen University Guangdong Province 518000 China School of Physics Electronics and Intelligent Manufacturing Huaihua University Hunan Huaihua418008 China College of Electronics and Information Engineering Shenzhen University Guangdong Province 518000 China Department of Physics and Astronomy College of Science King Saud University Riyadh11451 Saudi Arabia College of Chemistry and Environmental Engineering Shenzhen University Guangdong Province Shenzhen518055 China School of Electronic Engineering Nanjing Xiaozhuang University Nanjing211171 China

Designing ceramic fuel cells (CFCs) with fast ionic conduction and superior electrochemical performance at low temperatures is critical for advancing hydrogen applications. Here, we developed a heterostructure electrolyte by combining the ionic conductor Gd0.1Ce0.9O2 (GDC) with the semiconductor material CaTiO3 (CTO) to shape into the composite heterostructure (semiconductor ionic heterostructure) CTO-GDC. The designed heterostructure with different fermi levels established the depletion zone due to the redistribution of charges at the interface, leading to enhancement of the ionic conduction;meanwhile, the established built-in electric field suppresses the electronic conduction speed of the ion's transportation at the interface of the constructed heterostructure (CTO-GDC). The formation of heterostructure introduces a number of oxygen vacancies, as confirmed via x-ray photoelectron spectroscopy (XPS) and electron paramagnetic resonance (EPR), benefiting the transportation of ions in the composite heterostructure. The prepared composite heterostructure shows the highest power output of 810 mW/cm2 at a low operational temperature of 520 °C. The CTO-GDC shows high ionic conductivity of 0.17 S cm−1 at 520 °C and low activation energy of 0.785 eV at 520-420 °C. The composite containing a 50 % molar ratio of GDC and CTO demonstrated exceptional performance by successfully inhibiting electron transit, improving ionic conductivity, and achieving outstanding power output. The enhanced ionic conductivity with low activation energy of composite heterostructure suggests that designing a heterostructure seems an efficient approach to fuel cell application. © 2025

关键词： Paramagnetic resonance

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SCIPaD: Incorporating Spatial Clues into Unsupervised Pose-Depth Joint Learning

arXiv

引用

arXiv 2024年

作者： Feng, Yi Guo, Zizhan Chen, Qijun Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Research Institute for Intelligent Autonomous Systems Shanghai Institute of Intelligent Science and Technology The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

Unsupervised monocular depth estimation frameworks have shown promising performance in autonomous driving. However, existing solutions primarily rely on a simple convolutional neural network for ego-motion recovery, which struggles to estimate precise camera poses in dynamic, complicated real-world scenarios. These inaccurately estimated camera poses can inevitably deteriorate the photometric reconstruction and mislead the depth estimation networks with wrong supervisory signals. In this article, we introduce SCIPaD, a novel approach that incorporates spatial clues for unsupervised depth-pose joint learning. Specifically, a confidence-aware feature flow estimator is proposed to acquire 2D feature positional translations and their associated confidence levels. Meanwhile, we introduce a positional clue aggregator, which integrates pseudo 3D point clouds from DepthNet and 2D feature flows into homogeneous positional representations. Finally, a hierarchical positional embedding injector is proposed to selectively inject spatial clues into semantic features for robust camera pose decoding. Extensive experiments and analyses demonstrate the superior performance of our model compared to other state-of-the-art methods. Remarkably, SCIPaD achieves a reduction of 22.2% in average translation error and 34.8% in average angular error for camera pose estimation task on the KITTI Odometry dataset. Our source code is available at https://***/SCIPaD. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

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Online, Target-Free LiDAR-Camera Extrinsic Calibration via Cross-Modal Mask Matching

arXiv

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arXiv 2024年

作者： Huang, Zhiwei Zhang, Yikang Chen, Qijun Fan, Rui The Department of Control Science & Engineering The College of Electronics & Information Engineering Shanghai Institute of Intelligent Science and Technology Shanghai Research Institute for Intelligent Autonomous Systems The State Key Laboratory of Intelligent Autonomous Systems Frontiers Science Center for Intelligent Autonomous Systems Tongji University Shanghai201804 China

LiDAR-camera extrinsic calibration (LCEC) is crucial for data fusion in intelligent vehicles. Offline, target-based approaches have long been the preferred choice in this field. However, they often demonstrate poor adaptability to real-world environments. This is largely because extrinsic parameters may change significantly due to moderate shocks or during extended operations in environments with vibrations. In contrast, online, target-free approaches provide greater adaptability yet typically lack robustness, primarily due to the challenges in cross-modal feature matching. Therefore, in this article, we unleash the full potential of large vision models (LVMs), which are emerging as a significant trend in the fields of computer vision and robotics, especially for embodied artificial intelligence, to achieve robust and accurate online, target-free LCEC across a variety of challenging scenarios. Our main contributions are threefold: we introduce a novel framework known as MIAS-LCEC, provide an open-source versatile calibration toolbox with an interactive visualization interface, and publish three real-world datasets captured from various indoor and outdoor environments. The cornerstone of our framework and toolbox is the cross-modal mask matching (C3M) algorithm, developed based on a state-of-the-art (SoTA) LVM and capable of generating sufficient and reliable matches. Extensive experiments conducted on these real-world datasets demonstrate the robustness of our approach and its superior performance compared to SoTA methods, particularly for the solid-state LiDARs with super-wide fields of view. Our toolbox and datasets are publicly available at ***/MIAS-LCEC. Copyright © 2024, The Authors. All rights reserved.

关键词： Cameras

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Implementation of Rev1 and Rev2 Bug Family Algorithms in ROS Noetic

Implementation of Rev1 and Rev2 Bug Family Algorithms in ROS...

引用

Information, control, and Communication Technologies (ICCT), International Conference on

作者： Maksim Roslavtsev Alexander Eryomin Ramil Safin Evgeni Magid Department of Computer Engineering (DCE) Moscow Institute of Electronics and Mathematics Higher School of Economics Moscow Russian Federation Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russian Federation

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

Modern map-dependent algorithms for mobile robot navigation typically overload a CPU and memory with a gradually increasing amount of environmental data. In contrast, Bug family local path planning algorithms operate without mapping and have significantly lower hardware requirements. Bug algorithms use real-time measurements from visual and touch sensors to make immediate decisions on direction of the robot’s motion. This paper presents an implementation of Rev1 and Rev2 Bug algorithms for the Robot Operating System (ROS) Noetic framework with a virtual model of the TurtleBot3 Burger robot. Given algorithms are validated in Gazebo simulation using various convex and maze environments. The results demonstrate superiority of Rev1 method over Rev2 in trajectory length in convex maps. However, Rev2 finds shorter paths in maze type environments.

关键词： Visualization Navigation Operating systems Computer bugs Tactile sensors Real-time systems Trajectory Motion measurement Robots Testing

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Implementation and Validation of the CautiousBug Algorithm in ROS Noetic

Implementation and Validation of the CautiousBug Algorithm i...

引用

Information, control, and Communication Technologies (ICCT), International Conference on

作者： Roman Mishenin Alexander Eryomin Tatyana Tsoy Evgeni Magid Department of Computer Engineering (DCE) Moscow Institute of Electronics and Mathematics Higher School of Economics Moscow Russian Federation Laboratory of Intelligent Robotics Systems (LIRS) Institute of Information Technology and Intelligent Systems Kazan Federal University Kazan Russian Federation

ISBN: (数字)9798331517564

ISBN: (纸本)9798331517571

In this paper, we present an implementation of the CautiousBug algorithm within the Noetic distribution of the Robot Operating System (ROS). Bug algorithms address a challenge of robot navigation in unknown environments without relying on pre-existing maps or constructing new ones. These algorithms utilize odometry data, operate without a map, require minimal computational resources, and can be implemented on relatively simple hardware. A C++ software application was created to simulate a behavior of the CautiousBug algorithm in various environments within the Gazebo simulator. This application allows for an analysis of key metrics, including accumulated yaw, distance traversed and algorithm's runtime. We conducted a set of virtual experiments in the Gazebo to evaluate the CautiousBug performance.

关键词： Runtime Navigation Software architecture Working environment noise Operating systems Software algorithms Software Robustness Path planning Robots

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Comparison of Monocular ROS-Based Visual SLAM Methods 1

引用

7th International Conference on Interactive Collaborative robotics, ICR 2022

作者： Safarova, Liaisan Abbyasov, Bulat Tsoy, Tatyana Li, Hongbing Magid, Evgeni Laboratory of Intelligent Robotic Systems Intelligent Robotics Department Institute of Information Technology and Intelligent Systems Kazan Federal University Kremlyovskaya Str. 35 Kazan420111 Russia Department of Instrument Science and Engineering Shanghai Jiao Tong University Shanghai China Tikhonov Moscow Institute of Electronics and Mathematics HSE University Tallinn Str 34 Moscow123592 Russia

ISBN: (数字)9783031236099

ISBN: (纸本)9783031236082

Simultaneous Localization and Mapping (SLAM) is a robot navigation approach used to estimate a movement of a sensor in an unknown environment. SLAM application examples include urban search and rescue operations in high-risk environments, visual surveillance and service robotics. Compared to laser-range finders, visual sensors are more light weight, have less power consumption and provide more vast amount of environmental information. Visual SLAM methods are based on visual information only and employ monocular, stereo or RGD-D cameras as input sensors. Monocular SLAM methods are often preferred for a robotic platform when cost, energy and system weight requirements are limited. Calculation of errors and testing on ready-made datasets allow to check applicability of an algorithm in real-world scenarios with less efforts than experiments with a real robot. Verification of a sensor position and robot trajectory estimation accuracy is achieved by measuring Absolute Trajectory Error (ATE), Relative Pose Error (RPE) and Root Mean Square Error (RMSE). This article presents analysis and comparison of the most widely used Visual SLAM monocular algorithms built for Robot Operating System (ROS): ORB-SLAM2, ORB-SLAM3, DSO and LDSO. The KITTI and Euroc MAV datasets were selected to evaluate the algorithms’ performance. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Robot Operating System

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D3PRefiner: A Diffusion-based Denoise Method for 3D Human Pose Refinement

arXiv

引用

arXiv 2024年

作者： Yan, Danqi Gao, Qing Qian, Yuepeng Chen, Xinxing Fu, Chenglong Leng, Yuquan Shenzhen Key Laboratory of Biomimetic Robotics and Intelligent Systems the Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities China Department of Mechanical and Energy Engineering Southern University of Science and Technology Shenzhen518055 China School of Electronics and Communication Engineering Sun Yat-sen University Shenzhen518107 China

Three-dimensional (3D) human pose estimation using a monocular camera has gained increasing attention due to its ease of implementation and the abundance of data available from daily life. However, owing to the inherent depth ambiguity in images, the accuracy of existing monocular camera-based 3D pose estimation methods remains unsatisfactory, and the estimated 3D poses usually include much noise. By observing the histogram of this noise, we find each dimension of the noise follows a certain distribution, which indicates the possibility for a neural network to learn the mapping between noisy poses and ground truth poses. In this work, in order to obtain more accurate 3D poses, a Diffusion-based 3D Pose Refiner (D3PRefiner) is proposed to refine the output of any existing 3D pose estimator. We first introduce a conditional multivariate Gaussian distribution to model the distribution of noisy 3D poses, using paired 2D poses and noisy 3D poses as conditions to achieve greater accuracy. Additionally, we leverage the architecture of current diffusion models to convert the distribution of noisy 3D poses into ground truth 3D poses. To evaluate the effectiveness of the proposed method, two state-of-the-art sequence-to-sequence 3D pose estimators are used as basic 3D pose estimation models, and the proposed method is evaluated on different types of 2D poses and different lengths of the input sequence. Experimental results demonstrate the proposed architecture can significantly improve the performance of current sequence-to-sequence 3D pose estimators, with a reduction of at least 10.3% in the mean per joint position error (MPJPE) and at least 11.0% in the Procrustes MPJPE (P-MPJPE). Copyright © 2024, The Authors. All rights reserved.

关键词： Diffusion

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Equivalent input disturbance-based load frequency control for smart grid with air conditioning loads

引用

Science China(Information Sciences) 2022年第2期65卷 106-123页

作者： Li JIN Yong HE Chuan-Ke ZHANG Xing-Chen SHANGGUAN Lin JIANG Min WU School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Department of Electrical Engineering and Electronics University of Liverpool Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Integrating intermittent wind power into power systems results in low or zero inertia, threatening their frequency stability. To accommodate intermittent generations, the demand response(DR) is introduced, and air conditioning loads(ACs) account for an increasing proportion of all loads. The replacement of traditional generators with wind turbines and the ACs user uncertainties produce parameter uncertainties. This paper aims to construct an equivalent input disturbance(EID)-based load frequency control(LFC) strategy for the power system by considering wind power and ACs. First, an open-loop model is constructed for the LFC scheme with parameter uncertainties. Then, the parameter uncertainties and external disturbance are lumped into a fictitious disturbance, which is estimated using an EID *** incorporating the estimation of disturbance into the control input, the disturbance-rejection performance is achieved. Next, the Lyapunov theory is used to derive the two linear-matrix-inequality-based asymptotic stability criteria. A design algorithm is developed for the EID-based LFC scheme by exploiting an overall performance evaluation index. Finally, simulation results for the single-area and two-area LFC schemes show that, compared with the existing approaches, the method presented realizes the better disturbance rejection and higher robustness against parameter uncertainties, wind power fluctuation, and tie-line power ***, its robustness to time delays is verified.

关键词： equivalent input disturbance load frequency control parameter uncertainties wind power air conditioning loads

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Design and Implementation of Telemedicine System Using Light Fidelity and PIC16F877A Microcontroller 14

Design and Implementation of Telemedicine System Using Light...

引用

14th International Conference on Information Science and Technology, ICIST 2024

作者： Ezilarasan, M.R. Leung, Man-Fai Dai, Xiangguang Vel Tech Rangarajan Dr. Sagunthala R and D Instituteof Science and Technology Department of Electronics and Communication Engineering Chennai India School of Computing and Information Science Anglia Ruskin University Faculty of Science and Engineering Cambridge United Kingdom Information Processing and Control of Chongqing Municipal Institutions of Higher Education Chongqing Three Gorges University Key Laboratory of Intelligent Chongqing Wanzhou404100 China

ISBN: (纸本)9798350353334

Medical Body Area Networks (MBANs) increasingly utilize wireless communication technologies to enhance the freedom and convenience for patients and caregivers. Currently, radio frequency (RF) is the prevalent medium in healthcare applications;however, the potential for electromagnetic interference with precision medical equipment remains a concern. This study introduces a novel design and implementation of a medical healthcare information system using the newly developed Wireless Visible Light Communication (VLC) technology, also known as Light Fidelity (Li-Fi). Visible Light Emitting Diodes (LEDs), expected to soon surpass traditional incandescent and fluorescent bulbs as the primary light source due to their energy efficiency, facilitate this technology. In this research, patient health is monitored using sensors, with results displayed on an LCD. An LED lightbulb transmits the data as light signals, which are captured by a photo-detector at the receiver's end. This setup not only displays the output on an LCD but also alerts caregivers through an auditory signal, beeping every 15 seconds for respiration and every 30 seconds for heart rate monitoring. Moreover, these lighting fixtures serve dual functions: illumination and wireless data transmission, using the rapid switching capability of LEDs. This prototype VLC-based system offers a promising alternative for data services and monitoring in hospital areas where RF use is restricted. © 2024 IEEE.

关键词： Liquid crystal displays

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